5,693 research outputs found
CANCER TREATMENT BY TARGETING HDAC4 TRANSLOCATION INDUCED BY MICROSECOND PULSED ELECTRIC FIELD EXPOSURE: MECHANISTIC INSIGHTS THROUGH KINASES AND PHOSPHATASES
Epigenetic modifications, arising from sub-cellular shifts in histone deacetylase (HDAC) activity and localization, present promising strategies for diverse cancer treatments. HDACs, enzymes responsible for post-translational histone modifications, induce these epigenetic changes by removing acetyl groups from Δ-N-acetyl-lysine residues on histones, thereby suppressing gene transcription. Within the HDAC group, class IIa HDACs are notable for their responsiveness to extracellular signals, bridging the gap between external stimuli, plasma membrane, and genome through nuclear-cytoplasmic translocation. This localization offers two significant mechanisms for cancer treatment: nuclear accumulation of HDACs represses oncogenic transcription factors, such as myocyte-specific enhancer factor 2C (MEF2C), triggering various cell death pathways. Conversely, cytoplasmic HDAC accumulation acts similarly to HDAC inhibitors by silencing genes. My dissertation introduces an innovative approach for glioblastoma and breast cancer treatment by investigating the application of microsecond pulsed electric fields. It particularly focuses on HDAC4, a class IIa HDAC overexpressed in these cancers. Beyond demonstrating HDAC4 translocation, my research delves into the intricate roles of kinases and phosphatases, shedding light on the underlying factors governing HDAC4 translocation
Irish Ocean Climate and Ecosystem Status Report
Summary report for Irish Ocean Climate & Ecosystem Status Report also published here. This Irish Ocean Climate & Ecosystem Status
Summary for Policymakers brings together the
latest evidence of ocean change in Irish waters.
The report is intended to summarise the current
trends in atmospheric patterns, ocean warming,
sea level rise, ocean acidification, plankton and
fish distributions and abundance, and seabird
population trends. The report represents a
collaboration between marine researchers within
the Marine Institute and others based in Irelandâs
higher education institutes and public bodies. It
includes authors from Met Ăireann, Maynooth
University, the University of Galway, the Atlantic
Technological University, National Parks and
Wildlife, Birdwatch Ireland, Trinity College Dublin,
University College Dublin, Inland Fisheries Ireland,
The National Water Forum, the Environmental
Protection Agency, and the Dundalk Institute of
Technology.This report is intended to summarise the
current trends in Irelandâs ocean climate. Use
has been made of archived marine data held by
a range of organisations to elucidate some of
the key trends observed in phenomena such as
atmospheric changes, ocean warming, sea level
rise, acidification, plankton and fish distributions
and abundance, and seabirds. The report aims to
summarise the key findings and recommendations
in each of these areas as a guide to climate
adaptation policy and for the public. It builds on the
previous Ocean Climate & Ecosystem Status Report
published in 2010.
The report examines the recently published
literature in each of the topic areas and combines
this in many cases with analysis of new data sets
including long-term time series to identify trends
in essential ocean variables in Irish waters. In
some cases, model projections of the likely future
state of the atmosphere and ocean are presented
under different climate emission scenarios.Marine Institut
Recommended from our members
Sonic heritage: listening to the past
History is so often told through objects, images and photographs, but the potential of sounds to reveal place and space is often neglected. Our research project âSonic Palimpsestâ1 explores the potential of sound to evoke impressions and new understandings of the past, to embrace the sonic as a tool to understand what was, in a way that can complement and add to our predominant visual understandings. Our work includes the expansion of the Oral History archives held at Chatham Dockyard to include womenâs voices and experiences, and the creation of sonic works to engage the public with their heritage. Our research highlights the social and cultural value of oral history and field recordings in the transmission of knowledge to both researchers and the public. Together these recordings document how buildings and spaces within the dockyard were used and experienced by those who worked there. We can begin to understand the social and cultural roles of these buildings within the community, both past and present
ACC Saturator: Automatic Kernel Optimization for Directive-Based GPU Code
Automatic code optimization is a complex process that typically involves the
application of multiple discrete algorithms that modify the program structure
irreversibly. However, the design of these algorithms is often monolithic, and
they require repetitive implementation to perform similar analyses due to the
lack of cooperation. To address this issue, modern optimization techniques,
such as equality saturation, allow for exhaustive term rewriting at various
levels of inputs, thereby simplifying compiler design.
In this paper, we propose equality saturation to optimize sequential codes
utilized in directive-based programming for GPUs. Our approach simultaneously
realizes less computation, less memory access, and high memory throughput. Our
fully-automated framework constructs single-assignment forms from inputs to be
entirely rewritten while keeping dependencies and extracts optimal cases.
Through practical benchmarks, we demonstrate a significant performance
improvement on several compilers. Furthermore, we highlight the advantages of
computational reordering and emphasize the significance of memory-access order
for modern GPUs
Yet another Improvement of Plantard Arithmetic for Faster Kyber on Low-end 32-bit IoT Devices
This paper presents another improved version of Plantard arithmetic that
could speed up Kyber implementations on two low-end 32-bit IoT platforms (ARM
Cortex-M3 and RISC-V) without SIMD extensions. Specifically, we further enlarge
the input range of the Plantard arithmetic without modifying its computation
steps. After tailoring the Plantard arithmetic for Kyber's modulus, we show
that the input range of the Plantard multiplication by a constant is at least
2.45 times larger than the original design in TCHES2022. Then, two optimization
techniques for efficient Plantard arithmetic on Cortex-M3 and RISC-V are
presented. We show that the Plantard arithmetic supersedes both Montgomery and
Barrett arithmetic on low-end 32-bit platforms. With the enlarged input range
and the efficient implementation of the Plantard arithmetic on these platforms,
we propose various optimization strategies for NTT/INTT. We minimize or
entirely eliminate the modular reduction of coefficients in NTT/INTT by taking
advantage of the larger input range of the proposed Plantard arithmetic on
low-end 32-bit platforms. Furthermore, we propose two memory optimization
strategies that reduce 23.50% to 28.31% stack usage for the speed-version Kyber
implementation when compared to its counterpart on Cortex-M4. The proposed
optimizations make the speed-version implementation more feasible on low-end
IoT devices. Thanks to the aforementioned optimizations, our NTT/INTT
implementation shows considerable speedups compared to the state-of-the-art
work. Overall, we demonstrate the applicability of the speed-version Kyber
implementation on memory-constrained IoT platforms and set new speed records
for Kyber on these platforms
Deployment of Deep Neural Networks on Dedicated Hardware Accelerators
Deep Neural Networks (DNNs) have established themselves as powerful tools for
a wide range of complex tasks, for example computer vision or natural language
processing. DNNs are notoriously demanding on compute resources and as a
result, dedicated hardware accelerators for all use cases are developed. Different
accelerators provide solutions from hyper scaling cloud environments for the
training of DNNs to inference devices in embedded systems. They implement
intrinsics for complex operations directly in hardware. A common example
are intrinsics for matrix multiplication. However, there exists a gap between
the ecosystems of applications for deep learning practitioners and hardware
accelerators. HowDNNs can efficiently utilize the specialized hardware intrinsics
is still mainly defined by human hardware and software experts.
Methods to automatically utilize hardware intrinsics in DNN operators are a
subject of active research. Existing literature often works with transformationdriven
approaches, which aim to establish a sequence of program rewrites and
data-layout transformations such that the hardware intrinsic can be used to
compute the operator. However, the complexity this of task has not yet been
explored, especially for less frequently used operators like Capsule Routing. And
not only the implementation of DNN operators with intrinsics is challenging,
also their optimization on the target device is difficult. Hardware-in-the-loop
tools are often used for this problem. They use latency measurements of implementations
candidates to find the fastest one. However, specialized accelerators
can have memory and programming limitations, so that not every arithmetically
correct implementation is a valid program for the accelerator. These invalid
implementations can lead to unnecessary long the optimization time.
This work investigates the complexity of transformation-driven processes to
automatically embed hardware intrinsics into DNN operators. It is explored
with a custom, graph-based intermediate representation (IR). While operators
like Fully Connected Layers can be handled with reasonable effort, increasing
operator complexity or advanced data-layout transformation can lead to scaling issues.
Building on these insights, this work proposes a novel method to embed
hardware intrinsics into DNN operators. It is based on a dataflow analysis.
The dataflow embedding method allows the exploration of how intrinsics and
operators match without explicit transformations. From the results it can derive
the data layout and program structure necessary to compute the operator with
the intrinsic. A prototype implementation for a dedicated hardware accelerator
demonstrates state-of-the art performance for a wide range of convolutions, while
being agnostic to the data layout. For some operators in the benchmark, the
presented method can also generate alternative implementation strategies to
improve hardware utilization, resulting in a geo-mean speed-up of Ă2.813 while
reducing the memory footprint. Lastly, by curating the initial set of possible
implementations for the hardware-in-the-loop optimization, the median timeto-
solution is reduced by a factor of Ă2.40. At the same time, the possibility to
have prolonged searches due a bad initial set of implementations is reduced,
improving the optimizationâs robustness by Ă2.35
Elements of Ion Linear Accelerators, Calm in The Resonances, Other_Tales
The main part of this book, Elements of Linear Accelerators, outlines in Part
1 a framework for non-relativistic linear accelerator focusing and accelerating
channel design, simulation, optimization and analysis where space charge is an
important factor. Part 1 is the most important part of the book; grasping the
framework is essential to fully understand and appreciate the elements within
it, and the myriad application details of the following Parts. The treatment
concentrates on all linacs, large or small, intended for high-intensity, very
low beam loss, factory-type application. The Radio-Frequency-Quadrupole (RFQ)
is especially developed as a representative and the most complicated linac form
(from dc to bunched and accelerated beam), extending to practical design of
long, high energy linacs, including space charge resonances and beam halo
formation, and some challenges for future work. Also a practical method is
presented for designing Alternating-Phase- Focused (APF) linacs with long
sequences and high energy gain. Full open-source software is available. The
following part, Calm in the Resonances and Other Tales, contains eyewitness
accounts of nearly 60 years of participation in accelerator technology.
(September 2023) The LINACS codes are released at no cost and, as always,with
fully open-source coding. (p.2 & Ch 19.10)Comment: 652 pages. Some hundreds of figures - all images, there is no data in
the figures. (September 2023) The LINACS codes are released at no cost and,
as always,with fully open-source coding. (p.2 & Ch 19.10
Evolutionary genomics of cowpox virus and recombination in vitro between a naturally occurring cowpox virus and a vaccinia virus vectored influenza vaccine
Modified vaccinia virus Ankara (MVA) is a promising orthopoxvirus (OPXV) vector vaccine candidate due to its host range restriction and good safety profile as a smallpox vaccine. It has been widely tested in clinical trials as a recombinant vector for vaccination against infectious diseases and cancers in humans and animals. Furthermore, it is being used as a smallpox and Mpox vaccine. However, the extensive use of MVA and MVA vectored vaccines have the potential for MVA or MVA vectored vaccine to recombine with naturally circulating OPXV. Cowpox virus (CPXV) as a close relative of MVA is a potential candidate for recombination. Hence, the genetic diversity and evolution of CPXV was assessed in this work, as well as recombination in vitro between a naturally occurring CPXV and MVA vectored vaccine in cells in which MVA multiplies poorly. CPXV is classified as a single species; however, we demonstrated that CPXV might be an assemblage of several species based on its high genetic diversity, lack of monophyly, and close phylogenetic relationship with other OPXV. CPXV strains were separated into five major clusters rather than one monophyletic cluster. Furthermore, we described a new, distinct cluster closely related to Ectromelia virus (ECTV) and Abatino macacapox virus (Abatino) named âECTV-Abatino-like CPXVâ. Additionally, we showed evidence that a Norwegian CPXV isolate was a natural occurring recombinant CPXV that might have emerged following multiple recombination events between different OPXV species from the Old World and North America. Under in vitro conditions, the progeny viruses obtained from co-infection and superinfection of Vero cells with MVA-HANP and CPXV-No-F1 had mosaic genomes and displayed parental and non-parental plaque phenotypes. Furthermore, some progeny viruses contained the transgene from MVA-HANP and regained genes that were deleted or fragmented in MVA-HANP. Overall, these findings will contribute to the environmental risk assessment of MVA and MVA vectored vaccines and to the improvement of the biosafety of MVA vectored vaccines
Signal Processing Techniques for Radar Cross Section Measurements Using Orthogonal Frequency-Division Multiplexing Waveforms
In recent work conducted at the University of Oklahomaâs Advanced Radar Research Center, it has been shown that using orthogonal frequency-division multiplexing (OFDM) offers a significant time reduction in taking wideband radar cross section (RCS) measurements, compared with traditional techniques. This has led to an interest as to whether or not the reduced measurement time enables wideband RCS measurements of moving targets. In an attempt to answer this question, this thesis presents a simulation framework for RCS extraction of a moving target.
Because the target is moving, it is assumed that measurements are taken in an outdoor environment. As such, ground clutter is the primary competing interference. It is shown that in order to recover the target RCS, range-Doppler filtering must be performed. As a result, the filter shape, available Doppler resolution, and signal-to-noise ratio become the primary determiners of performance. Some closed-form expressions are derived to help determine acceptable system parameters and improve performance.
Interfering signals from other transmitters are also considered in this work. It is shown that if an interfering signal corrupts part of the spectrum, filtering is impossible because the target cannot be located in the range-Doppler space. To combat this, the spectrum is nulled at points where interference occurs. This enables filtering to be applied; however, nulls will exist in the RCS measurement. Finally, some spectral reconstruction techniques are discussed and tested with the purpose of estimating pieces of the spectrum that were lost
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